Tl;dr - Optimizing the orchestration of intent data first requires constantly updating and maintaining integrated data from multiple sources in a full marketing data stack. A core function of this process is to unify contact data to create a single master, or "Golden Record." That's a deceptively complex, and important challenge - and it's an often overlooked step in the process of using intent data.
Creating a "Golden Record"
Let's start with basics.
What is contact data unification? Contact data unification is the persistent process of taking all your marketing and sales data points (from your properties and various purchased data) and weaving them together to create accurate master records (often called Golden Records) for each contact, across devices, locations, activities, and profiles. The process is persistent because you'll often accumulate new data which isn't identical to existing data, and must be unified.
Why is data unification important? Without unification you will often have multiple records for a single contact. This prevents you from understanding the full buyers profile and journey, and limits your ability to orchestrate the data.
It sounds simple. And in the rush to start with intent data, it's often overlooked as folks press to put their new, exciting data to work.
That's an oversight, and the unification process is deceptively complex.
While most marketing automation systems dedupe by email address, they stumble when data isn't associated with an email, or when there's a typo, or when old and new work emails conflict with personal emails. Cookies can help, but they don't solve for all the issues.
Robust contact data unification is one of the primary functions of a CDP (customer data platform). CDPs originated in the B2C space where unification tends to be tougher. Although there's a dearth of purpose built B2B CDPs, as long as you can associate contacts with accounts, then the contact data unification function of any CDP should be adequate for intent data optimization.
How Is That Relevant to Intent Data Orchestration?
Often, intent data itself is of limited value. Rather it's the broader context, the inferences, the insights derived from a full marketing data stack, and effective integration that enable the insights which unlock the value. It's important to understand four elements - the contact fit and activity and the account fit and activity.
Imagine having three different sets of contact activity (with an associated email with one format, an associated email with a different format, and without an associated email) which are really only one person, taking multiple actions. This creates challenges.
In the process of orchestrating your data, you're probably going to segment by established levels of individual activity, and aggregate activity across a certain number of people at the account level. If you wanted to see activity from three people at the account level, but didn't unify contact data from the example above into a Golden Record, you might trigger orchestration based on one person with three non-unified profiles.
Your theoretical segment in that case might be well designed, but the data would let you down and you'd proceed (probably investing in ads, diverting BDR attention, etc) based on a faulty application of the data.
In other words, if you want the engine to run smoothly on all cylinders (what's the electric motor equivalent?) you have to unify contact data.
So What's Involved in Contact Data Unification?
First you have to "ingest" the data - pull it into your Martech systems, or into a centralized system (like a CDP) which also ingests your first party data, for full integration of first and second party data, along with enrichment, technographics, etc. Many intent data providers suggest you use their platform (often selling it as an ABM software solution) - that reduces the value of the data because it typically ignores all your first party data which is resident in your marketing automation and CRM systems.
Once the data is ingested, then the unification process runs. This must be continuous since you'll often have new data for contacts and accounts which will have to be matched.
Unification typically looks at various factors including IP, cookie ID, name, email, company and more.
How Does Data Unification Impact Orchestration?
As noted above orchestration is going to rely on segmentation based on a combination of account fit and activity, and contact fit and activity.
Account fit will be determined by firmographics, technographics, and other factors relevant to your situation. Contact fit will be determined by job title (function, seniority) and other possible factors. Activity will be determined by the number and types of activities by a contact, and in aggregate by various contacts in the company, and, of course, other factors.
Here's where it gets interesting.
Once a contact has been added to a segment, presumably you're going to take action - some combination of assigning them to a rep, showing them a segment of ads, launching a specific contextually appropriate outbound sales cadence, etc.
The sales enablement decisions and actions which you'll "orchestrate" at scale, will all hinge on accurately quantifying and qualifying the contact activities.
That's why contact data unification is key to optimized intent data orchestration.
A Note on Contact Level™ Intent Data
You might be thinking to yourself "We've been running intent data for years and never stopped to think about this."
You might be right. Here's why.
Most intent data is account level data only. In other words it hints at what accounts might be in market, and then your marketing and sales work to discover who within the account might be leading or participating in a project. It is inherently inneficient.
IntentData.io's data is actually contact level - providing information on the person (including job title) and detailed, granular insight on the actions they took.
That's a powerful difference. And it's one that takes some additional capability to leverage.
Where you might activate account level data by simply prioritizing accounts for ad campaigns, contact level intent data enables much more sophisticated targeting - for paid ads, outbound campaigns and other approaches.
As soon as you start to think about it, though, you often realize that even if you only use account level data, in fact integrating a full data stack, running the segmentation logic, and triggering orchestrated activities requires capability beyond many contact centric marketing automation and CRM platforms. If you've bought an ABM ad platform because your tech stack couldn't do the same thing, you know what I mean.
So I predict that a CDP is in your future anyway, and if you're wondering about optimizing orchestration of contact level intent data at scale, the contact data unification step will be important.